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    Real time road traffic monitoring system using mobile devices

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    Thesis, Undergraduate (550.1Kb)
    Date
    2007-07
    Author
    Ajwang, Monica
    Kiwanuka, Edwin
    Nakaziba, Loy Persis
    Nakisige, Jackie
    Opio, Philip Omadi
    Masambu, Ronald
    Ntwatwa, Joel Benjamin
    Asiimwe, Penelope Beene
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    Abstract
    This is a report on a Real-Time Road Traffic Monitoring System. The study was done to establish an effective and efficient way of delivering real time road traffic information to motorists. The focus was on developing a mobile application capable of calculating the best paths from a given point to a destination. Since traffic is not static, we decided wireless technology as the best technology to deliver information; that is, delivering information to the motorists‟ mobile devices, either PDAs or mobile phones. Our objectives were; to find out the parameters used in quantification of road traffic, to implement an algorithm capable of calculating best alternative route from a given point and to implement a system that receives road traffic values, processes the values and disseminate real-time information on request. We limited our scope to the routes from Mulago heading to Nakawa. Our methods included making visual observation to find out the speeds of cars at traffic points; that is where traffic starts to build up on routes. Interviews; at CPS, Radio One, were done to find out how current traffic monitoring systems in Kampala quantify traffic. Document examination was done to find out parameters being used by current real-time traffic monitoring systems, as well as to assess the applicability of such systems in Kampala. We then invoked Dijkstra‟s algorithm which solves shortest path problems (mainly applied in routing). Our design language was WML used in conjunction with PHP to realize the application. Our developed system was able to capture road values by observation of traffic officials, process the data and disseminate the real-time information to the motorists‟ wireless devices on demand. However, we recommend more effective ways of capturing data other than visual observation by traffic officials given that humans are prone to error.
    URI
    http://hdl.handle.net/10570/814
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    • School of Computing and Informatics Technology (CIT) Collection

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